interpret (for the three analyses), clust_tab and
mean_sd_tab all return one
tabxplor table, so it can be piped, filtered and exported like any other. What differs is
only how it is shown:
options(tabxplor.print = "html") draws it with tab_html: the
Viewer pane in RStudio/Positron, a real html table when knitted. The default, "console",
prints the plain tabxplor grid. It is the same option that governs an ordinary crosstab
— one to set, once, at the top of a script — and it is read at print time, so it can be set
after the table is built. For a text file or a language model, pipe the table into
tab_md explicitly. An html summary of axes carries no hover
tooltip — every figure one would reveal already has a column of its own — while
clust_tab, being a crosstab of percentages, keeps them: the count behind each one
is worth hovering for.
An analysis-of-axes summary carries the eigenvalues as a subordinate table
(set_footer_tabs), which every medium renders under it: the percentage of
variance of each axis, its cumulated percentage, and for an MCA Benzecri's modified rate — the
numbers the rule for choosing how many axes to interpret is read on.
eig = FALSE leaves them out, for a document that shows them already or prints the summary
several times to comment it column by column; n_axes says how many of them to print. When
some axes are left out — by n_axes, or because ncp truncated the analysis — a
final row states how many the cloud has (... of 27). A table showing every axis carries no
such row. The Total row is always the whole cloud: 100 % and the total inertia.
min_contrib moves the threshold: NULL (the default) keeps the points contributing
more than the mean — Le Roux and Rouanet's rule — 0 keeps them all, and a number keeps
what contributes at least that many percent. The summary row's label follows it, so it can never
name a set it does not total — and in a correspondence analysis, where each axis carries two
such rows, it leads with the margin's own name (Rows: above mean ctr, or the name
vars gave it). color = FALSE builds the table with no colour measure at all.
lang is NULL (the session's language), "en" or "fr": it
translates what a reader reads as prose — the axis heading, the summary row's label, the words
the colour legend uses and the glossary lines under it. Column names are never
translated: they are the tibble's own names, and a name that changed with the language could not
be indexed. These words are fixed when the table is built, so an export asking for the
other language (tab_md(lang = )) gets tabxplor's grammar translated and ggfacto's nouns as
they were written: build the table in the language you will print it in.
complete = TRUE widens an MCA or CA summary: each side of the axis gains the point's
coordinate (its sign says which pole, its size how far out) and its cos2 (the
share of the point's own variance the axis holds), plus the spread between the two sides.
Neither is coloured there: a coordinate in axis standard deviations has no conventional cut-off,
and an MCA cloud has so many axes that every cos2 is small — the 50 % / 75 % rule a
interpret table of a PCA reads does not transfer. Both are read by comparing the points
shown; only the contribution carries an absolute threshold.
Usage
# S3 method for class 'ggfacto_summary'
print(x, ...)Arguments
- x
A table returned by one of the functions of [ggfacto_summary].
- ...
Passed to
tab_html, or to the console print method.
The footer
The colour legend is tabxplor's, saying ggfacto's nouns — a factorial axis has no
chi-squared, so set_legend_words re-states what the ladder grades and
nothing else. It is therefore built at render, in the language and the palette of the call that
prints it, with its coloured swatches, in all five media. Nothing to suppress: a call
written by hand is just interpret(res.mca) |> tab_md(css = FALSE, print = FALSE).
Under it, one plain line names each statistic the colours do not grade.
After a dplyr verb
The subclass is not carried by dplyr (only a table's tabxplor attributes are), so a summary
that has been through mutate() prints as an ordinary tabxplor table — the
eigenvalues still render under it, and the format is the same options(tabxplor.print)
either way. What is lost is only the hover policy and the margin names.